Modeling First Order Systems with Footage of a Small Motorized Cart
Audience
Course module will be deployed sometime during the 2023-2024 academic year.
The expected class size is around 50 students.
Students are expected to have experience with system modeling, finding the time constant and gain of a first-order system, and general understanding of MATLAB. This module is not suitable for students with no math or science background.
Other applicable courses that may benefit from this module:
This module could be used in other classes where understanding systems is not necessary, but explanations of how to find the time constant and gain would need to be included.
Project Summary
Primary Objective
Through this module students should learn how to obtain system parameters from data, evaluate the linearity of a system, investigate sources of uncertainty that arise when using real-world data, and reflect on data aggregation.
Goals
Have students collect data from videos
Have students analyze data they collected to obtain system parameters
Aggregate class data to create a larger data set
Draw conclusions about the system based on the parameters
Reflect on the sources of variability in system and process
Content Outline
This module has 2 components: The individual data collection and analysis, and then drawing conclusions based on the aggregated class data. The system examined is the open loop response of a small motorized cart with a voltage applied to the motor.
Individual Components*: Students will complete parts 1 and 2 individually and upload their results to a linked google form
Data collection - students will use visual tracking software to collect data on videos of cart runs
Software link: https://physlets.org/tracker/
Part 1: Finding system parameters in MatLab
Part 2: Individual Analysis
Class Components*: Students will complete parts 3 and 4 after the class data has been uploaded.
Part 3: Comparative Class Analysis
Part 4: Reflection Questions
*Students will submit their answers to all the numbered questions in a report on Canvas or a Canvas equivalent.
For more information email: difuse-pi-group@dartmouth.edu
